MLOps / AI Engineer

Job Title

MLOps / AI Engineer Experience: 8 10 Years

Job Summary Looking for an experienced MLOps / AI Engineer to build, deploy, and manage enterprise AI/ML platforms and production-grade ML/LLM applications. The ideal candidate should have expertise in Python, Azure ML, Docker, Kubernetes, CI/CD, MLOps, LLMs, RAG, and cloud platforms (Azure/AWS/GCP). Key Responsibilities

• Build and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, retraining, and lifecycle management.
• Develop ML models using Python and Azure Machine Learning.
• Deploy AI workloads using Docker and Kubernetes.
• Build CI/CD pipelines and automate infrastructure using Terraform/Bicep/ARM/CloudFormation.
• Develop LLM & Generative AI solutions using RAG, Prompt Engineering, Embeddings, Vector Databases, and Agentic AI.
• Integrate with Azure OpenAI, OpenAI, Anthropic Claude, or AWS Bedrock.
• Monitor model performance, drift, logging, tracing, and production health.
• Implement security, IAM, secrets management, encryption, and governance.
• Provide production support and incident resolution.

Mandatory Skills

• 8 10 years of MLOps / AI Engineering experience.
• Python & Linux.
• Azure ML / AWS / GCP.
• Docker & Kubernetes.
• CI/CD (GitHub Actions, Azure DevOps, Jenkins).
• Terraform / ARM / Bicep / CloudFormation.
• MLflow / Kubeflow / SageMaker / Azure ML.
• LLMs, RAG, Prompt Engineering, Embeddings, Vector Databases.
• Azure OpenAI / OpenAI / Anthropic / AWS Bedrock.
• Monitoring, Model Drift, Observability.

Good-to-Have Skills

• Agentic AI Frameworks.
• MLflow / Kubeflow.
• Prometheus, Grafana, CloudWatch, Azure Monitor.
• ITIL / Production Support.
• High Availability AI Platforms.

Education

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Information Technology, or related field.